Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add taizen-ai/taizen-claude-plugins --skill product-contextgit clone --depth 1 https://github.com/taizen-ai/taizen-claude-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/taizen-ai/taizen-claude-plugins/product-context)<a href="https://agentmods.dev/skills/taizen-ai/taizen-claude-plugins/product-context"><img src="https://agentmods.dev/badge/skills/taizen-ai/taizen-claude-plugins/product-context/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/taizen-ai/taizen-claude-plugins/product-context"><img src="https://agentmods.dev/badge/skills/taizen-ai/taizen-claude-plugins/product-context.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00035 | $0.02030 |
| Opus 5 | $0.00017 | $0.01015 |
| Sonnet 5 | $0.00007 | $0.00406 |
| Haiku 4.5 | $0.00003 | $0.00203 |
Grade A, and why
product-context scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 338 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Context Skill
Foundational product marketing context that all GTM skills reference for positioning, messaging, and voice consistency.
Purpose
Provide the source of truth for product positioning, target audience, messaging framework, and brand voice. Other skills automatically reference this context to ensure consistency across all GTM outputs.
Note: This is a background reference skill that Claude auto-loads when other GTM skills need product context. It is not meant to be invoked directly by users. To create or update your product context document, use the
messaging-positioningorbrand-voiceskills.
Skills That Reference This Context
The following skills automatically use product-context to ensure consistency:
copywriting- Uses messaging framework and brand voiceemail-sequences- Applies value propositions and tonesocial-content- Maintains brand voice across channelsnewsletter-writer- References messaging pillars and voiceseo-content- Uses positioning and key differentiatorscompetitive-intelligence- References positioning against competitorsbuyer-profiles- Aligns persona messaging with frameworkdiscovery-prep- Uses value props for tailored questionssales-playbook- References positioning for talk tracksoutreach-templates- Applies messaging to prospectingcase-study-builder- Uses value pillars for storytellingroi-builder- References value metrics and proof points
Required Integrations
Setup: Connect these data sources to enable full functionality. Claude will prompt you to connect any missing integrations when you use this skill.
Data Sources
# PRODUCT CONTEXT DATA SOURCES
# Configure the sources for your product foundation
# Enterprise Search (searches across all internal sources)
- source: enterprise_search
connector: "{{GLEAN | MOVEWORKS | ELASTIC}}"
data:
- internal_docs
- wiki_content
- shared_drives
# Product Documentation
- source: product_docs
connector: "{{GOOGLE_DRIVE | SHAREPOINT | NOTION | CONFLUENCE}}"
paths:
- "/Product/Documentation/"
- "/Product/Roadmap/"
- "/Product Marketing/"
# Marketing Foundation
- source: marketing_docs
connector: "{{GOOGLE_DRIVE | SHAREPOINT | NOTION}}"
paths:
- "/Marketing/Brand Guidelines/"
- "/Marketing/Messaging/"
- "/Marketing/Positioning/"
# Customer Research
- source: customer_research
connector: "{{GOOGLE_DRIVE | SHAREPOINT | NOTION}}"
paths:
- "/Research/Persona Research/"
- "/Research/ICP Documentation/"
- "/Research/Customer Interviews/"
# Competitive Intelligence
- source: competitive_intel
connector: "{{KLUE | CRAYON | KOMPYTE}}"
data:
- competitor_overview
- market_landscape
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 338 lines · 35 tokens per session scan A 46ca5d81bf35
product-context is a skill published in the GitHub repository taizen-ai/taizen-claude-plugins (8 stars, last pushed 3mo ago), licensed MIT. It adds 35 tokens to every session and 2,030 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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